With or without force? : European public opinion on democracy promotion

A Large part of the education provided at colleges and universities of today requires for thestudent to be more independent in their studies. This demands that the physical space,where the students choose to study, is designed in a way that can encourage and supportlearning. It seems as though that many of the learning spaces of today don’t always meetthe students’ needs. The university library at the University of Umeå is currently planningto design new learning spaces for the students. The aim of this study is to examine how thephysical learning space can be designed to engage and encourage the students in theirlearning process. Based on literature describing learning spaces we have initially identified three mainareas to examine- Learning, Information Technology and Learning space design. Theseareas are all important features in the design of new learning spaces. With informationdrawn from that literature we conducted an empirical study at the library of the Universityof Umeå. The empirical study was carried out through observations and focus groupinterviews. To give us more insight about the students’ thoughts about the learning spacewe also compared our findings with a survey conducted by the library personnel in 2008and 2010. The result of our study shows that there are some areas to be improved in theexisting learning space. The students are working more collaboratively which requiresmore group areas. Our study also shows that flexibility, more student interaction and asocial and engaging environment are all important features in the design of new learningspaces

On Structural Parameterizations of the Bounded-Degree Vertex Deletion Problem

We study the parameterized complexity of the Bounded-Degree Vertex Deletion problem (BDD), where the aim is to find a maximum induced subgraph whose maximum degree is below a given degree bound. Our focus lies on parameters that measure the structural properties of the input instance. We first show that the problem is W[1]-hard parameterized by a wide range of fairly restrictive structural parameters such as the feedback vertex set number, pathwidth, treedepth, and even the size of a minimum vertex deletion set into graphs of pathwidth and treedepth at most three. We thereby resolve an open question stated in Betzler, Bredereck, Niedermeier and Uhlmann (2012) concerning the complexity of BDD parameterized by the feedback vertex set number. On the positive side, we obtain fixed-parameter algorithms for the problem with respect to the decompositional parameter treecut width and a novel problem-specific parameter called the core fracture number

Automatic Domain Adaptation for Parsing

Current statistical parsers tend to perform well only on their training domain and nearby genres. While strong performance on a few related domains is sufficient for many situations, it is advantageous for parsers to be able to generalize to a wide variety of domains. When parsing document collections involving heterogeneous domains (e.g. the web), the optimal parsing model for each document is typically not obvious. We study this problem as a new task — multiple source parser adaptation. Our system trains on corpora from many different domains. It learns not only statistics of those domains but quantitative measures of domain differences and how those differences affect parsing accuracy. Given a specific target text, the resulting system proposes linear combinations of parsing models trained on the source corpora. Tested across six domains, our system outperforms all non-oracle baselines including the best domain-independent parsing model. Thus, we are able to demonstrate the value of customizing parsing models to specific domains.